Industrial Sectors

Every industry is characterised by its specific requirements. It takes the right combination of industry experience and innovative analytics to produce powerful solutions and tailored big data strategies.

Industry 4.0 / Industrial Analytics

Industrial production generates huge amounts of data which facilitate innovative services such as preventative maintenance, quality analyses in real time and better control processes. Big Data analytics enables predictive and prescriptive analyses, makes influencing factors and dependencies easier to understand and also makes it possible to analyse massive sensory data in real time. Analysts and engineers working in cooperation succeed in improving products, optimising processes and convincing customers.


Like no other, the automotive sector is characterised by contrasting ends of the spectrum: emotion and technology. A vehicle’s production cycle – from development through production to quality monitoring – is dominated by highly complex technical data whereas the (after) sales market is heavily characterised by customers’ emotions and desires. By analysing each of these contrasting dimensions it is possible to keep your finger on the pulse of both customers and technology.


In the logistics sector quite a number of different types of information can be relevant. In addition to diverse internal data within the logistics chain itself it may also need to account for traffic updates, weather forecasts, information about end customers, the world economy and much more. An integrated analysis gives us a clear picture of how the business is managed. With that comes an understanding of current patterns in real time and the ability to forecast future developments.


The financial sector is facing a major upheaval because of innovative technology – the so called »Fintechs«. However, data-driven solutions also open up new possibilities for more traditional aspects of the industry. Fraudulent behaviour, breach of compliance targets or wrongly assessed risks are very difficult to detect in real time using conventional procedures. So experts have very much had to rely on gut instinct to be able to find the needle in the haystack. The same applies to your own customers – it is only when you expand your view to include market data, news and social media that you begin to understand them properly.


Health insurance companies and healthcare providers/hospitals already deal with a vast array of data relating to diagnoses, treatment processes and billing issues. By adding external data sources, however, from socio-demographic data to discussions on online patient forums, many more influencing factors can now be taken into consideration. They can help to analyse the progression of a disease and infer medically relevant findings. Fraudulent attempts can be recognised more systematically, medicine controlling can be supported and resources can be planned more efficiently.